Concurrent data structures are essential in modern multi-threaded applications. They allow multiple threads to access and manipulate shared data without creating race conditions or other synchronization issues. Traditionally, synchronization primitives like locks, mutexes, and condition variables have been used to achieve thread-safe access to data. However, these primitives can be error-prone and can result in complex, hard-to-maintain code.

In recent years, C++20 introduced coroutines as a language feature. Coroutines simplify asynchronous programming by allowing developers to write code that looks sequential but executes concurrently. This makes coroutines a powerful tool for implementing concurrent data structures.

What are C++ Coroutines?

Coroutines are a language feature that allows suspension and resumption of execution at predefined points. They are similar to functions but with the ability to pause execution and later resume from where they left off. This makes coroutines perfect for designing asynchronous code structures.

Implementing Concurrent Data Structures with C++ Coroutines

When designing concurrent data structures using coroutines, the key idea is to leverage suspension and resumption of coroutines to achieve fine-grained synchronization without explicit locks. Instead of using locks to protect critical sections, coroutines use suspension to wait for resources to become available.

Consider a simple concurrent queue implementation. Traditionally, a mutex and condition variables are used to synchronize access to the queue. However, with coroutines, we can achieve the same level of synchronization in a more efficient and concise manner.

Here’s an example implementation of a concurrent queue using C++ coroutines:

#include <coroutine>
#include <queue>
#include <mutex>

template <typename T>
class ConcurrentQueue {
public:
    struct Promise;

    using CoroutineHandle = std::coroutine_handle<Promise>;

    struct Promise {
        T value;
        CoroutineHandle next;

        std::queue<T> queue;
        std::mutex mutex;

        auto yield_value(T v) {
            value = v;
            return std::suspend_always{};
        }

        auto get_return_object() {
            return CoroutineHandle::from_promise(*this);
        }

        auto initial_suspend() {
            return std::suspend_never{};
        }

        auto final_suspend() noexcept {
            return std::suspend_always{};
        }

        void return_void() {}

        void unhandled_exception() {
            std::terminate();
        }

        bool enqueue(T v) {
            std::lock_guard<std::mutex> lock(mutex);
            queue.push(v);
            return !next;
        }

        bool dequeue(T& v) {
            std::lock_guard<std::mutex> lock(mutex);
            if (queue.empty())
                return false;
            v = std::move(queue.front());
            queue.pop();
            return true;
        }
    };

    explicit ConcurrentQueue() : handle(nullptr) {}

    ~ConcurrentQueue() {
        if (handle)
            handle.destroy();
    }

    auto pop() {
        return handle->yield_value(T{});
    }

    bool try_pop(T& value) {
        return handle->dequeue(value);
    }

    bool push(T value) {
        if (handle)
            return handle->enqueue(std::move(value));
        return false;
    }

    CoroutineHandle handle;
};

In the above code, the ConcurrentQueue class defines a coroutine promise struct, which manages the suspension and resumption of the coroutine. The promise struct contains a queue and a mutex to protect the critical section of enqueue and dequeue operations. Yielding the coroutine using yield_value waits for the next available value, while resuming the coroutine pushes the value to the queue.

Conclusion

C++ coroutines provide a powerful mechanism for implementing concurrent data structures. By leveraging suspension and resumption of execution, coroutines can achieve fine-grained synchronization without explicit locks. This leads to more concise and efficient code, making coroutines an excellent choice for designing multi-threaded applications.

#programming #concurrency